When I saw that there was a plan for a whole bunch of unmanned, semi-autonomous racecars to compete at the Indianapolis Motor Speedway (Indy, or IMS) racetrack, I initially thought we might be headed to one significant mess of broken-up machines and potentially a lot of damage. I tracked the various announcements of the competition as things progressed, especially when a prize of $1 million dollars was put up by the Lilly Endowment in Indianapolis, and the majority of the field appeared to be potentially staffed by undergrad university teams.
However, this isn’t the first time we’ve had unmanned, autonomous road vehicles in competition — we’ve seen highly instrumented SUVs in desert settings in Nevada and California, initially with pretty poor results, which began to improve significantly for the second time round, then vehicles in some simulated street settings with some mixed and also some pretty good results.
So, as the competition date grew closer for the Indy Autonomous Challenge (IAC), the number of published progress reports began to increase, and we began to better understand how the initial 40 teams might take on this seemingly impossible task — how on Earth will they replicate a regular Indy (also a class of racecar) race? Surely many unmanned racecars on the same track at the same time doing more than 150 mph would be catastrophic!
When you take a look, however, at the advances we’ve seen, which have enabled unmanned cars, trucks, taxis and such – surely this tech could stretch to meet these major objectives? But Dallara AV-21 Indy Light racecars avoiding hurtling walls passing by, cornering, getting in and out of the pits, coping with vehicles behind, ahead and overtaking — even a superior-equipped unmanned racecar at >150 mph — well that’s something we would really need to see.
Then you have to take a look at the outfits involved, providing support to the IAC teams – companies including Cisco, and motor sport units such as ADLINK, Ansys, Aptiv, Bridgestone, Luminar, Microsoft and Valvoline and the non-profit Energy Systems Network. The University teams from around the world themselves appeared to also have significant heritage and skill-levels.
As the 40 University teams started the long trek to get over the hurdles that this challenge presented, members from 21 of those institutions were actually able to make it to Indy, grouped into nine “national” teams. By October 23 the nine teams, with only one car each, were ready to test their autonomous vehicles on the actual track.
Clemson University established the baseline Dallara AV-21 vehicle and technology to be used by each team for the race, with sensors monitoring chassis motion, suspension, tires and powertrain. Each team would install its own guidance and avoidance system, with each vehicle equipped with six cameras, four lidars, RTK GNSS, associated radios and bags of computing running each team’s customized control system software. The object being for cars to exit pit-lane, accelerate, brake, establish an optimum line for each corner and flat, avoid obstacles, evaluate the track conditions and establish tolerable limits.
The teams were required to complete several stages of selection, from submission of initial proposals through demonstration of existing vehicle automation capability, simulated race performance, qualification testing at the Indy track — all leading to an anticipated head-to head race against the other qualifiers.
Then 20 days of planned testing stretched to 50, and three months of preparation passed with students working intensely throughout, curing the glitches, experimenting with how to increase lap speed, and pushing the limits while still keeping the cars intact.
Energy Systems Network managed the rules of the final competition in a way that reflected Indy qualification days prior the main race — they judged that the technology was not yet at a stage where multiple cars on the track at the same time would have been such a good idea. So, each car was to individually run a number of practice/qualification laps and the quickest car would be the winner.
During the first stage of live competition, cars were required to exit the pits and run a warmup lap, followed by two laps that were timed and a slow-down lap that required navigating around inflatable barriers on the front-stretch, and then return successfully back around the track into their pit-stop locations. There were several spins in the corners and several crashes, but the four surviving cars/teams were able to optimistically post speeds of more than 130 mph.
The final phase involved the four teams taking their cars around a number of warm-up/practice laps, followed by four timed laps. Only the car from Germany’s Technical University of Munich was able to complete all laps with an average speed of ~136 mph, so that team ultimately won the $1 million prize. Even so, all teams were able to successfully mature their systems’ performance through the many months leading up to the IAC and their progress through the various qualification stages. Even the other three final qualifiers had much to celebrate as a result of the competition.
The sponsors supporting the various teams as they progressed through the Challenge may have spent more than $120 million, so that high-pressure development work will be invested back into many vehicle automation opportunities. After all, that was the main objective for the whole undertaking. We should hopefully begin to see safer, more capable self-driving vehicles emerge in the months to come as the technology is applied to more production vehicle automation.
Tony Murfin
GNSS Aerospace
